AI RESEARCH

Exactness Matters for Physical Rule Enforcement

arXiv CS.LG

ArXi:2605.08285v1 Announce Type: new Autoregressive scientific forecasters often enforce physical or structural constraints by repairing each predicted state before feeding it back into the model. However, it remains unclear when stronger physical rule enforcement becomes reliable and when it becomes a source of distribution shift. We study this question through operator exactness, meaning whether the repair map is the identity on the target manifold and is aligned with the target geometry.